Data Warehouse Developer Interview Questions UK: 8 Real Questions and What Interviewers Want

Most Data Warehouse Developer interviews in the UK follow a pattern, and knowing it beats guessing. Below are eight questions from our bank of 12, each with a note on what the interviewer is really after.

Eight Data Warehouse Developer interview questions, and what the interviewer is thinking

1. What are the different types of fact table, and how do you decide on the grain?

Why they ask: Choosing grain and fact type correctly is the foundation of a sound warehouse design.

2. How do you handle late-arriving facts and dimension members that do not exist yet when the fact arrives?

Why they ask: It is a routine data quality problem that reveals whether you design for real-world data.

3. What does a typical day as a Data Warehouse Developer involve?

Why they ask: They want to confirm you understand the combination of design, development and support.

4. How would you use clustered columnstore indexes and table partitioning to improve a large fact table in SQL Server?

Why they ask: Physical design decisions have a huge effect on query speed and load times.

5. How would you load a very large fact table efficiently each night while keeping the warehouse available for users?

Why they ask: Load design directly affects reliability and the batch window.

6. A key management report that used to run in two minutes now takes over twenty, as data volumes have grown. How would you investigate?

Why they ask: Query tuning is a regular task, and they want a methodical approach rather than guesswork.

7. The business redefines what counts as an active customer and wants three years of history restated. How would you handle it in the warehouse?

Why they ask: Changing definitions is common and tests your approach to history, lineage and communication.

8. Tell me about a time you reconciled warehouse figures to a source system and found a discrepancy.

Why they ask: Accuracy and reconciliation discipline are essential for a trusted warehouse.

A sample answer to question 1

What are the different types of fact table, and how do you decide on the grain?

Grain defines exactly what one row represents, such as one order line or one account per month, and I always settle it first, in discussion with the business, because every dimension and measure must be consistent with it. Mixing grains in one fact table leads to double counting. There are three main types. A transaction fact table records one row per event, such as a sale, and is the most detailed. A periodic snapshot records the state at regular intervals, for example the balance of every account at month end, which suits trend analysis of things that don't change through events. An accumulating snapshot has one row per process instance, such as an order moving through placed, picked, shipped and delivered, with several date columns updated as milestones occur. I choose the type by asking what question the business needs answered, and I aim to store the lowest practical grain so aggregates can be built from it.

Common mistake to avoid: Mixing grains in one table; Choosing a type before understanding the question

Want the rest?

Full model answers, key points and common mistakes for all 12 questions are on the Data Warehouse Developer interview questions page. The first five are free, no sign-up needed.